{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "from sklearn.cluster import MiniBatchKMeans\n",
    "from sklearn.cluster import KMeans\n",
    "from sklearn.cluster import DBSCAN\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn import metrics\n",
    "\n",
    "from sklearn.decomposition import PCA\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import warnings\n",
    "\n",
    "warnings.filterwarnings('ignore')\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "events = pd.read_csv('new_events.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(13418, 110)"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "events.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>event_id</th>\n",
       "      <th>user_id</th>\n",
       "      <th>start_time</th>\n",
       "      <th>city</th>\n",
       "      <th>state</th>\n",
       "      <th>zip</th>\n",
       "      <th>country</th>\n",
       "      <th>lat</th>\n",
       "      <th>lng</th>\n",
       "      <th>c_1</th>\n",
       "      <th>...</th>\n",
       "      <th>c_92</th>\n",
       "      <th>c_93</th>\n",
       "      <th>c_94</th>\n",
       "      <th>c_95</th>\n",
       "      <th>c_96</th>\n",
       "      <th>c_97</th>\n",
       "      <th>c_98</th>\n",
       "      <th>c_99</th>\n",
       "      <th>c_100</th>\n",
       "      <th>c_other</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>684921758</td>\n",
       "      <td>3647864012</td>\n",
       "      <td>2012-10-31T00:00:00.001Z</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>244999119</td>\n",
       "      <td>3476440521</td>\n",
       "      <td>2012-11-03T00:00:00.001Z</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3928440935</td>\n",
       "      <td>517514445</td>\n",
       "      <td>2012-11-05T00:00:00.001Z</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2582345152</td>\n",
       "      <td>781585781</td>\n",
       "      <td>2012-10-30T00:00:00.001Z</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1051165850</td>\n",
       "      <td>1016098580</td>\n",
       "      <td>2012-09-27T00:00:00.001Z</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 110 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     event_id     user_id                start_time city state  zip country  \\\n",
       "0   684921758  3647864012  2012-10-31T00:00:00.001Z  NaN   NaN  NaN     NaN   \n",
       "1   244999119  3476440521  2012-11-03T00:00:00.001Z  NaN   NaN  NaN     NaN   \n",
       "2  3928440935   517514445  2012-11-05T00:00:00.001Z  NaN   NaN  NaN     NaN   \n",
       "3  2582345152   781585781  2012-10-30T00:00:00.001Z  NaN   NaN  NaN     NaN   \n",
       "4  1051165850  1016098580  2012-09-27T00:00:00.001Z  NaN   NaN  NaN     NaN   \n",
       "\n",
       "   lat  lng  c_1   ...     c_92  c_93  c_94  c_95  c_96  c_97  c_98  c_99  \\\n",
       "0  NaN  NaN    2   ...        0     1     0     0     0     0     0     0   \n",
       "1  NaN  NaN    2   ...        0     0     0     0     0     0     0     0   \n",
       "2  NaN  NaN    0   ...        0     0     0     0     0     0     0     0   \n",
       "3  NaN  NaN    1   ...        0     0     0     0     0     0     0     0   \n",
       "4  NaN  NaN    1   ...        0     0     0     0     0     0     0     0   \n",
       "\n",
       "   c_100  c_other  \n",
       "0      0        9  \n",
       "1      0        7  \n",
       "2      0       12  \n",
       "3      0        8  \n",
       "4      0        9  \n",
       "\n",
       "[5 rows x 110 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "events.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "drops = ['event_id','user_id','start_time','city','state','zip','country','lat','lng']\n",
    "X_train = events.drop(drops,axis=1).values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(13418, 101)"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X_train.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### MiniBatchKMeans 聚类"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "def K_cluster_analysis(K, X_train):\n",
    "    \n",
    "    mb_kmeans = MiniBatchKMeans(n_clusters = K)\n",
    "    mb_kmeans.fit(X_train)\n",
    "    \n",
    "    y_pred = mb_kmeans.predict(X_train)\n",
    "\n",
    "    ch_scores = metrics.calinski_harabaz_score(X_train,y_pred)\n",
    "    \n",
    "    print(\"clusters: {}\".format(K))\n",
    "    print(\"ch_scores: {}\".format(ch_scores))\n",
    "    \n",
    "    return ch_scores"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "clusters: 10\n",
      "ch_scores: 1110.5608735424512\n",
      "clusters: 20\n",
      "ch_scores: 811.4503239990485\n",
      "clusters: 30\n",
      "ch_scores: 344.64959762018697\n",
      "clusters: 40\n",
      "ch_scores: 304.45142623952523\n",
      "clusters: 50\n",
      "ch_scores: 272.57656442612114\n",
      "clusters: 60\n",
      "ch_scores: 575.5169091035037\n",
      "clusters: 70\n",
      "ch_scores: 150.98397964368615\n",
      "clusters: 80\n",
      "ch_scores: 342.0987831667667\n",
      "clusters: 90\n",
      "ch_scores: 252.77792713453073\n",
      "clusters: 100\n",
      "ch_scores: 124.35169844430646\n",
      "clusters: 200\n",
      "ch_scores: 133.08121420007632\n",
      "clusters: 300\n",
      "ch_scores: 46.045372285122085\n"
     ]
    },
    {
     "data": {
      "image/png": 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ApWGzpcDq8HxNeE14/zHnymM2m2IFwHBHAAFMnuynhd62rbBlEpHKVYjrAP4SuN7MuvBt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\nSEIpAEREEup/ATeHsWCZyq7xAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1a0ca13c18>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 设置超参数（聚类数目K）搜索范围\n",
    "Ks = [10, 20, 30,40,50,60,70,80,90,100,200,300]\n",
    "ch_score = []\n",
    "for K in Ks:\n",
    "    \n",
    "    ch = K_cluster_analysis(K, X_train)\n",
    "    ch_score.append(ch)\n",
    "\n",
    "plt.plot(Ks, np.array(ch_score), 'b-')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x10937a5f8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 聚类可视化,初始clusters为10\n",
    "\n",
    "colors = ['b','g','r','k','c','m','y','#e24fff','#524C90','#845868']\n",
    "\n",
    "n_clusters = 10\n",
    "mb_kmeans = MiniBatchKMeans(n_clusters = n_clusters)\n",
    "mb_kmeans.fit(X_train)\n",
    "\n",
    "y_train = mb_kmeans.labels_\n",
    "cents = mb_kmeans.cluster_centers_\n",
    "\n",
    "x_axis = range(X_train.shape[1])\n",
    "plt.scatter(X_train[:, 0], X_train[:, 1], c=y_train)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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KMBzeVnZjtq1so66PUNG4hEMAAABAU47qHLox6xy6uXBjhIrGJRwCAAAAmnLU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\nnEA9vxq7IwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1093a8e10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(20,10)) \n",
    "for i in range(n_clusters):\n",
    "    \n",
    "    index = np.nonzero(y_train==i)[0]\n",
    "    xs_i = X_train[index]\n",
    "    \n",
    "    for j in range(min(len(xs_i),20)):\n",
    "        plt.plot(np.array(x_axis), xs_i[j], colors[i])\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 数据的取值以及方差太大,对数据进行标准化再进行聚类"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "from sklearn.preprocessing import StandardScaler\n",
    "ss_X = StandardScaler()\n",
    "X_train_ss = ss_X.fit_transform(X_train)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "clusters: 10\n",
      "ch_scores: 290.5029106524492\n",
      "clusters: 20\n",
      "ch_scores: 180.62638345542842\n",
      "clusters: 30\n",
      "ch_scores: 116.79291443851379\n",
      "clusters: 40\n",
      "ch_scores: 98.73241960700089\n",
      "clusters: 50\n",
      "ch_scores: 88.39600046060481\n",
      "clusters: 60\n",
      "ch_scores: 74.37606060767077\n",
      "clusters: 70\n",
      "ch_scores: 79.67719134328341\n",
      "clusters: 80\n",
      "ch_scores: 68.80925731168895\n",
      "clusters: 90\n",
      "ch_scores: 66.40531426501333\n",
      "clusters: 100\n",
      "ch_scores: 61.099001679593464\n"
     ]
    },
    {
     "data": {
      "image/png": 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P9vEscPkxYyfaFq4Aega3ccCUaqvC3XWr4o3iU0hHAOuADsFYB2Bd2LXV0u/f\nKdhgLwXmAUbxBSD1gucHA6+HXWctrYtmwEaC418x48m6bXQEcoBWFJ/8MQ8YmUzbB8UNHleXty0A\nfwC+U9ZyVb1pj76KzCwD6A+8SwXbP0TQJOA+oCh43BrY5e6Hg8e5FP+HTwbdgDzg/4KprGeC60yS\ncttw90+BX1N8qvVWoABYQfJuH3DibaHkQ7FEta0XBX0VmFkq8DJwl7vvDrueMJjZ1cB2d18RO1zG\noslyelc94Fxgirv3B/aQJNM0ZQnmn0cBXYHTgCYUT1EcK1m2j5Opsf83CvpKMrP6FIf8DHefHQxv\nC9o+UNH2DxFwAfDN4LsJXqR4+mYS0MLMSq7T6AR8Fk55tS4XyHX3d4PHf6U4+JNx2wAYDmx09zx3\nPwTMBs4nebcPOPG2kAt0jlmu2taLgr4SrPhy4D8Ba939NzFPJV37B3f/ibt3cvcMig+yveHuY4Al\nwLXBYkmxLgDc/XMgx8zOCIaGAR+RhNtGYAswyMwaB/9vStZHUm4fgRNtC3OA7wVn3wwCCkqmeKpK\nF0xVgpldCLwFZHFkXvqnFM/TzwLSCdo/uPvOUIoMgZldDPyXu19tZt0o3sNvBawExrr7gTDrqy1m\n1g94BkgBNgA3U7xTlZTbhpk9DFxP8dlqK4EfUjz3HPntw8xmAhdT3KFyG/AQ8DfK2BaCD8LfUnyW\nzl7gZnfPrJY6FPQiItGmqRsRkYhT0IuIRJyCXkQk4hT0IiIRp6AXEYk4Bb2ISMQp6EVEIk5BLyIS\ncf8P2UpDKJPE6W0AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1a1871bc18>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "Ks = [10, 20, 30,40,50,60,70,80,90,100]\n",
    "ch_score = []\n",
    "for K in Ks:\n",
    "    ch = K_cluster_analysis(K, X_train_ss)\n",
    "    ch_score.append(ch)\n",
    "plt.plot(Ks, np.array(ch_score), 'g-')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "clusters: 2\n",
      "ch_scores: 1471.4104038872679\n",
      "clusters: 3\n",
      "ch_scores: 776.5550215822363\n",
      "clusters: 4\n",
      "ch_scores: 627.6359993338527\n",
      "clusters: 5\n",
      "ch_scores: 480.05811944202753\n",
      "clusters: 6\n",
      "ch_scores: 524.251191453992\n",
      "clusters: 7\n",
      "ch_scores: 399.9916597770479\n",
      "clusters: 8\n",
      "ch_scores: 354.7123538068975\n",
      "clusters: 9\n",
      "ch_scores: 345.48580830317957\n",
      "clusters: 10\n",
      "ch_scores: 275.824432517465\n"
     ]
    },
    {
     "data": {
      "image/png": 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MMWaun+l3FBGRau0DWEpwZ+5KYJ33XNOAKcDPzSyX4Bz/i96PvAi08MZ/DvyyGrnD0rDO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\nRK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1a18896a90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "Ks = [2,3,4,5,6,7,8,9,10]\n",
    "ch_score = []\n",
    "for K in Ks:\n",
    "    ch = K_cluster_analysis(K, X_train_ss)\n",
    "    ch_score.append(ch)\n",
    "plt.plot(Ks, np.array(ch_score), 'g-')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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SwVttZpJ0v6Rnpn1zURTvKori0aIoHj127NgCm2GTlQvB2G1lVfMphNe09MbG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lP8gkNDQ2D16ClllFWrwqeVMVBcsgSB28iIvd15eTkc8fvvx7guXYrXFi7E2AdxWKIKd6uiFi0V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BvvGcpqersuTPhoa05EzEBbe87xeLgSdtRJ3327hRPz+dcfa2GbWIu/Ze588PcGtu1qjTokV4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M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\nAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1a0be82908>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "colors = ['b','r']\n",
    "\n",
    "n_clusters = 2\n",
    "mb_kmeans = MiniBatchKMeans(n_clusters = n_clusters)\n",
    "mb_kmeans.fit(X_train_ss)\n",
    "\n",
    "y_train = mb_kmeans.labels_\n",
    "cents = mb_kmeans.cluster_centers_\n",
    "\n",
    "x_axis = range(X_train.shape[1])\n",
    "\n",
    "plt.figure(figsize=(20,10)) \n",
    "for i in range(n_clusters):\n",
    "    index = np.nonzero(y_train==i)[0]\n",
    "    xs_i = X_train_ss[index]\n",
    "    for j in range(min(len(xs_i),500)):\n",
    "        plt.plot(np.array(x_axis), xs_i[j], colors[i])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x1a18dd3ef0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.scatter(X_train_ss[:, 0], X_train_ss[:, 1], c=y_train)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 考虑到有噪声数据,且 k-means 对于噪声点异常敏感,所以再用密度聚类进行分析"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "def DBSCAN_analysis( X_train, eps = 0.5, min_samples = 5):\n",
    "\n",
    "    \n",
    "    \n",
    "    dbscan = DBSCAN(eps = eps,min_samples = min_samples)\n",
    "    \n",
    "    y_pred = dbscan.fit_predict(X_train)\n",
    "    \n",
    "    y=  pd.DataFrame(y_pred)\n",
    "    \n",
    "    ch_score = metrics.calinski_harabaz_score(X_train,y_pred)\n",
    "    \n",
    "    print(\"DBSCAN begin with eps {}  min_samples {}\".format(eps,min_samples))\n",
    "    print(\"ch_score: {}\".format(ch_score))\n",
    "    print(y.apply(pd.value_counts))\n",
    "    \n",
    "    return ch_score"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "DBSCAN begin with eps 8  min_samples 5\n",
      "ch_score: 269.5156598097357\n",
      "        0\n",
      " 0  10412\n",
      "-1   2982\n",
      " 1      8\n",
      " 3      6\n",
      " 4      5\n",
      " 2      5\n",
      "DBSCAN begin with eps 12  min_samples 5\n",
      "ch_score: 1349.5584050489863\n",
      "        0\n",
      " 0  12239\n",
      "-1   1179\n",
      "DBSCAN begin with eps 16  min_samples 5\n",
      "ch_score: 607.5295520819501\n",
      "        0\n",
      " 0  12941\n",
      "-1    472\n",
      " 1      5\n",
      "DBSCAN begin with eps 20  min_samples 5\n",
      "ch_score: 972.7672175271275\n",
      "        0\n",
      " 0  13201\n",
      "-1    217\n",
      "DBSCAN begin with eps 24  min_samples 5\n",
      "ch_score: 792.4051502891882\n",
      "        0\n",
      " 0  13305\n",
      "-1    113\n",
      "DBSCAN begin with eps 28  min_samples 5\n",
      "ch_score: 674.3871527892939\n",
      "        0\n",
      " 0  13357\n",
      "-1     61\n",
      "DBSCAN begin with eps 30  min_samples 5\n",
      "ch_score: 640.7411094232775\n",
      "        0\n",
      " 0  13370\n",
      "-1     48\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x1a18885240>]"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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egGoBjO8ynrX711b5VaaW7lrKy2teZmSHkbxwywtVumxVMSLCLZG3MGvwLA4/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\nSvkpLQCllPJT/x/l6odYHIzBUAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1a18d37b70>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "eps_list = [8,12,16,20,24,28,30]\n",
    "ch_score = []\n",
    "\n",
    "\n",
    "for eps in eps_list:\n",
    "    score = DBSCAN_analysis(X_train_ss,eps)\n",
    "    ch_score.append(score)\n",
    "    \n",
    "plt.plot(eps_list, np.array(ch_score), 'g-')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 采用密度聚类分析数据集,可以看到 ch_score 得分高的时候,DBSCAN簇也划分为2类"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "dbc_kmeans = DBSCAN(eps = 12,min_samples = 5)\n",
    "dbc_kmeans.fit(X_train_ss)\n",
    "\n",
    "y_train = dbc_kmeans.labels_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x1a18d2e240>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.scatter(X_train_ss[:, 0], X_train_ss[:, 1], c=y_train)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
